shinkan-jinkendo/backend/tests/test_planning_problematic_slots.py
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Enhance Path QA and Progression Review Logic
- Introduced `_resolve_hint_major_index` to accurately map hints to major step indices, improving the handling of optimization hints in path evaluations.
- Added `_problematic_slots_from_path_qa` to identify and categorize problematic slots based on baseline QA, enhancing the quality assessment process.
- Updated `_slot_suggestion_accepted` to incorporate new parameters for slot problems and stage specifications, refining the decision-making process for slot suggestions.
- Enhanced `ProgressionGraphEditor` to improve user notifications regarding identified issues and suggestions, ensuring clearer communication of path evaluation results.
- Modified `buildProgressionComparePayload` and `buildUnifiedSlotReviewComparePayload` to support baseline evaluations, streamlining the comparison process for proposed paths.
2026-06-13 10:39:52 +02:00

54 lines
1.6 KiB
Python

"""Schachstellen-Erkennung für unified Slot-Review."""
from planning_exercise_path_builder import (
_problematic_slots_from_path_qa,
_slot_suggestion_accepted,
)
from planning_progression_roadmap import StageSpecArtifact
def _spec(midx: int) -> StageSpecArtifact:
return StageSpecArtifact(
major_step_index=midx,
learning_goal=f"Lernziel Slot {midx + 1}",
load_profile=[],
exercise_type="",
success_criteria=[],
anti_patterns=[],
)
def test_problematic_slots_from_optimization_hints():
qa = {
"optimization_hints": [
{
"action": "rematch_slot",
"step_index": 1,
"issue": "stage_mismatch",
"reason": "Übung passt nicht zur Stufe",
}
],
"off_topic_steps": [],
}
steps = [
{"roadmap_major_step_index": 0, "exercise_id": 1, "title": "A"},
{"roadmap_major_step_index": 1, "exercise_id": 2, "title": "B"},
]
specs = [_spec(0), _spec(1)]
problems = _problematic_slots_from_path_qa(qa, steps, specs)
assert 1 in problems
assert any("Stufe" in r or "passt" in r for r in problems[1])
def test_slot_suggestion_accepted_for_problem_slot():
diff = {"baseline_exercise_id": 10, "proposed_exercise_id": 99}
assert _slot_suggestion_accepted(
baseline_qa={"optimization_hints": [{"action": "rematch_slot", "roadmap_major_step_index": 1}]},
projected_qa={"optimization_hints": []},
baseline_score=0.7,
projected_score=0.7,
diff=diff,
off_topic=False,
major_idx=1,
slot_problem=True,
)